Understanding the performance behavior of a NoSQL database like Apache Cassandra™ under various conditions is critical. Conducting a formal proof of concept (POC) in the environment in which the database will run is the best way to evaluate platforms. POC processes that include the right benchmarks such as production configurations, parameters and anticipated data and concurrent user workloads give both IT and business stakeholders powerful insight about platforms under consideration and a view for how business applications will perform in production.

Independent benchmark analyses and testing of various NoSQL platforms under big data, production-level workloads have been performed over the years and have consistently identified Apache Cassandra as the platform of choice for businesses interested in adopting NoSQL as the database for modern Web, mobile and IOT applications.

One benchmark analysis (Solving Big Data Challenges for Enterprise Application Performance Management) by engineers at the University of Toronto, which in evaluating six different data stores, found Apache Cassandra the “clear winner throughout our experiments”.
Also, End Point Corporation, a database and open source consulting company, benchmarked the top NoSQL databases including: Apache Cassandra, Apache HBase, Couchbase, and MongoDB using a variety of different workloads on AWS EC2.

The databases involved were:

Apache Cassandra: Highly scalable, high performance distributed database designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure.

Apache HBase: Open source, non-relational, distributed database modeled after Google’s BigTable and is written in Java. It is developed as part of Apache Software Foundation’s Apache Hadoop project and runs on top of HDFS (Hadoop Distributed File System), providing BigTable-like capabilities for Hadoop.

MongoDB: Cross-platform document-oriented database system that eschews the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas making the integration of data in certain types of applications easier and faster.

End Point conducted the benchmark of these NoSQL database options on Amazon Web Services EC2 instances, which is an industry-standard platform for hosting horizontally scalable services. In order to minimize the effect of AWS CPU and I/O variability, End Point performed each test 3 times on 3 different days. New EC2 instances were used for each test run to further reduce the impact of any “lame instance” or “noisy neighbor” effects sometimes experienced in cloud environments, on any one test.

NoSQL Database Performance Testing Results

When it comes to performance, it should be noted that there is (to date) no single “winner takes all” among the top NoSQL databases or any other NoSQL engine for that matter. Depending on the use case and deployment conditions, it is almost always possible for one NoSQL database to outperform another and yet lag its competitor when the rules of engagement change. Here are a couple snapshots of the performance benchmark to give you a sense of how each NoSQL database stacks up.

Throughput by Workload

Each workload appears below with the throughput/operations-per-second (more is better) graphed vertically, the number of nodes used for the workload displayed horizontally, and a table with the result numbers following each graph.

Load process

For load, Couchbase, HBase, and MongoDB all had to be configured for non-durable writes to complete in a reasonable amount of time, with Cassandra being the only database performing durable write operations. Therefore, the numbers below for Couchbase, HBase, and MongoDB represent non-durable write metrics.

Nodes

Cassandra

HBase

MongoDB

Couchbase

1

18,683.43

15,617.98

8,368.44

13,761.12

2

31,144.24

23,373.93

13,462.51

26,140.82

4

53,067.62

38,991.82

18,038.49

40,063.34

8

86,924.94

74,405.64

34,305.30

76,504.40

16

173,001.20

143,553.41

73,335.62

131,887.99

32

326,427.07

296,857.36

134,968.87

192,204.94

Mixed Operational and Analytical Workload

Note that Couchbase was eliminated from this test because it does not support scan operations (producing the error: “Range scan is not supported”).

These performance metrics are just a few of the many that have solidified Apache Cassandra as the NoSQL database of choice for businesses needing a modern, distributed database for their Web, mobile and IOT applications. Each database option (Cassandra, HBase, Couchbase and MongoDB) will certainly shine in particular use cases, so it’s important to test your specific use cases to ensure your selected database meets your performance SLA.
Whether you are primarily concerned with throughput or latency, or more interested in the architectural benefits such as having no single point of failure or being able to have elastic scalability across multiple data centers and the cloud, much of an application’s success comes down to its ability to deliver the response times Web, mobile and IOT customers expect.

As the benchmarks referenced here showcase, Cassandra’s reputation for fast write and read performance, and delivering true linear scale performance in a masterless, scale-out design, bests its top NoSQL database rivals in many use cases.